Neural Network Speech Recognition System

Neural networks emerged as an attractive acoustic modeling approach in ASR in the late 1980s. Since then, neural networks have been used
in many aspects of speech recognition such as phoneme classification, isolated word recognition, and speaker adaptation. In contrast to HMMs, neural
networks make no assumptions about feature statistical properties and have several qualities making them attractive recognition models for speech recognition.
When used to estimate the probabilities of a speech feature segment, neural networks allow discriminative training in a natural and efficient manner.
Few assumptions on the statistics of input features are made with neural networks.